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Current unsupervised image-to-image translation techniques struggle to focus their attention on individual objects without altering the background or the way multiple objects interact within a scene. Motivated by the important role of…
The Human visual perception of the world is of a large fixed image that is highly detailed and sharp. However, receptor density in the retina is not uniform: a small central region called the fovea is very dense and exhibits high…
Astrometry is one of the main science case which drives the requirements of the next multiconjugate adaptive optics (MCAO) systems for future extremely large telescopes. The small diffraction limited point-spread function (PSF) and the high…
Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment. To tackle this problem, we introduce a new technique called…
This paper focuses on improving object detection performance by addressing the issue of image distortions, commonly encountered in uncontrolled acquisition environments. High-level computer vision tasks such as object detection,…
Existing approaches for unsupervised metric learning focus on exploring self-supervision information within the input image itself. We observe that, when analyzing images, human eyes often compare images against each other instead of…
Recent studies have revealed various manifestations of position bias in transformer architectures, from the "lost-in-the-middle" phenomenon to attention sinks, yet a comprehensive theoretical understanding of how attention masks and…
Current theories of perception suggest that the brain represents features of the world as probability distributions, but can such uncertain foundations provide the basis for everyday vision? Perceiving objects and scenes requires knowing…
Can human reading comprehension be assessed from eye movements in reading? In this work, we address this longstanding question using large-scale eyetracking data over textual materials that are geared towards behavioral analyses of reading…
During scene perception our eyes generate complex sequences of fixations. Predictors of fixation locations are bottom-up factors like luminance contrast, top-down factors like viewing instruction, and systematic biases like the tendency to…
Near distances are overestimated in virtual reality, and far distances are underestimated, but an explanation for these distortions remains elusive. One potential concern is that whilst the eye rotates to look at the virtual scene, the…
In this paper, we present an analysis of eye gaze patterns pertaining to visual cues in augmented reality (AR) for head-mounted displays (HMDs). We conducted an experimental study involving a picking and assembly task, which was guided by…
This study proposes a few-shot personalized saliency prediction method that leverages interpersonal gaze patterns. Unlike general saliency maps, personalized saliency maps (PSMs) capture individual visual attention and provide insights into…
We conducted an eye-tracking study where 30 participants performed searches on the web. We measured their topical knowledge before and after each task. Their eye-fixations were labelled as "reading" or "scanning". The series of reading…
Humans navigate and understand complex visual environments by subconsciously quantifying what they see, a process known as visual enumeration. However, traditional studies using flat screens fail to capture the cognitive dynamics of this…
Selective attention enables humans to efficiently process visual stimuli by enhancing important elements and filtering out irrelevant information. Locating visual attention is fundamental in neuroscience with potential applications in…
A visual hard attention model actively selects and observes a sequence of subregions in an image to make a prediction. The majority of hard attention models determine the attention-worthy regions by first analyzing a complete image.…
A recently proposed model observer mimics the foveated nature of the human visual system by processing the entire image with varying spatial detail, executing eye movements and scrolling through slices. The model can predict how human…
The spreading of attention has been proposed as a mechanism for how humans group features to segment objects. However, such a mechanism has not yet been implemented and tested in naturalistic images. Here, we leverage the feature maps from…
This work proposes a biologically inspired approach that focuses on attention systems that are able to inhibit or constrain what is relevant at any one moment. We propose a radically new approach to making progress in human-robot joint…